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On the Use of the Beta Distribution for a Hybrid Time Series Segmentation Algorithm

Authors

DURAN ROSAL, ANTONIO MANUEL, Dorado-Moreno, Manuel , Gutierrez, Pedro A. , Hervas-Martinez, Cesar

External publication

Si

Means

Lect. Notes Comput. Sci.

Scope

Proceedings Paper

Nature

Científica

JCR Quartile

SJR Quartile

SJR Impact

0.339

Publication date

01/01/2016

ISI

000387750600039

Abstract

This paper presents a local search (LS) method based on the beta distribution for time series segmentation with the purpose of correctly representing extreme values of the underlying variable studied. The LS procedure is combined with an evolutionary algorithm (EA) which segments time series trying to obtain a given number of homogeneous groups of segments. The proposal is tested on a real problem of wave height estimation, where extreme high waves are frequently found. The results show that the LS is able to significantly improve the clustering quality of the solutions obtained by the EA. Moreover, the best segmentation clearly groups extreme waves in a separate cluster and characterizes them according to their centroid.

Keywords

Time series segmentation; Evolutionary algorithms; Clustering; Extreme value distributions